Dynamic Audio-Visual Client Recognition modelling

This paper contains a report on an Visual Client Recognition System using Matlab software whichidentifies five clients and can be improved to identify as many clients as possible depending onthe number of clients it is trained to identify which was successfully implemented. Theimplementation was accomplished first by visual recognition system implemented using ThePrincipal Component Analysis, Linear Discriminant Analysis and Nearest Neighbor Classifier. Asuccessful implementation of second part was achieved by audio recognition using Mel-Frequency Cepstrum Coefficient, Linear Discriminant Analysis and Nearest Neighbor Classifierthe system was tested using images and sounds that have not been trained to the system to seewhether it can detect an intruder which lead us to a very successful result with précised responseto intruder and also explored another means implementing the visual recognition section using aNeural Network The work on visual recognition system was converted into a simulink block setwhich was then implemented in a Signal wave.